Modeling and Analysis of the Electrical Signal Transmission Mechanism of an Electronic Analgesic Apparatus

Objective: This study analyzes the transmission of the current signal of an electronic analgesic apparatus in arm muscles and provides a theoretical foundation for electrical stimulation analgesia. Methods: By combining human anatomy and tissue structure, a numerical simulation-based finite element model of the electronic analgesic apparatus is established using a frustum, cylinder, and ellipsoid as geometric entities in COMSOL Multiphysics 5.5. In the frequency domain environment, the transmission mechanism of the signal in the arm is analyzed by inputting current signals of 100 kHz, 1 MHz, and 10 MHz with an amplitude of ±20 mA. Results: With a continuous increase in carrier frequency, the effect of skin tissue becomes increasingly clear, and the signal becomes increasingly concentrated in the part of the skin that contacts the electrode. Moreover, diffusion inside the volume conductor loses consistency. At 100 kHz, as the communication distance from the electrode center gradually increases, the signal spreads more evenly within the arm. Conclusions: In the process of implementing a muscle soreness treatment using the electronic analgesic apparatus, a higher communication frequency makes it more difficult for the signal to enter the interior of the body and degrade the consistency of the signal. Therefore, the signal electrode should be placed as close as possible to the analgesic target area during the implementation of electric current analgesia.

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Publication Details

Journal
Recent Advances in Computer Science and Communications
Published
2024-12-11
DOI
https://doi.org/10.2174/0126662558337431241129093951
Primary Topic
Neuroscience and Neural Engineering
Type
article
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article

Modeling and Analysis of the Electrical Signal Transmission Mechanism of an Electronic Analgesic Apparatus

Zhenhui Li, Qi Wei, Shuang Zhang, Xiaoqi Li et al.
Recent Advances in Computer Science and Communications
Neuroscience and Neural Engineering
article

Modeling and Analysis of the Electrical Signal Transmission Mechanism of an Electronic Analgesic Apparatus

Zhenhui Li, Qi Wei, Shuang Zhang, Xiaoqi Li, Shuke Nie, Liming Huang, J. J. Qin
article en

Abstract

Objective: This study analyzes the transmission of the current signal of an electronic analgesic apparatus in arm muscles and provides a theoretical foundation for electrical stimulation analgesia. Methods: By combining human anatomy and tissue structure, a numerical simulation-based finite element model of the electronic analgesic apparatus is established using a frustum, cylinder, and ellipsoid as geometric entities in COMSOL Multiphysics 5.5. In the frequency domain environment, the transmission mechanism of the signal in the arm is analyzed by inputting current signals of 100 kHz, 1 MHz, and 10 MHz with an amplitude of ±20 mA. Results: With a continuous increase in carrier frequency, the effect of skin tissue becomes increasingly clear, and the signal becomes increasingly concentrated in the part of the skin that contacts the electrode. Moreover, diffusion inside the volume conductor loses consistency. At 100 kHz, as the communication distance from the electrode center gradually increases, the signal spreads more evenly within the arm. Conclusions: In the process of implementing a muscle soreness treatment using the electronic analgesic apparatus, a higher communication frequency makes it more difficult for the signal to enter the interior of the body and degrade the consistency of the signal. Therefore, the signal electrode should be placed as close as possible to the analgesic target area during the implementation of electric current analgesia.

Recent Advances in Computer Science and CommunicationsVol. 18(5)
Neijiang Normal University (CN)
Openalex Percentile: Top 76%
Neuroscience and Neural Engineering
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Modeling and Analysis of the Electrical Signal Transmission Mechanism of an Electronic Analgesic Apparatus — Zhenhui Li, Qi Wei, et al. · Recent Advances in Computer Science and Communications (2024) | TGRS Research Map | TGRS